You Will Begin With Your Own Internet And Walden Library

You Will Begin With Your Own Internet Andor Walden Library Search For

You will begin with your own Internet and/or Walden Library search for 1 or 2 current and credible articles on the various types of data resources, processes, and/or storage systems used in information systems in businesses big and small in various industries. There are many popular, relevant periodicals to search from as well. Some examples include: Information Week Wired Business 2.0 Business Week Post your research findings: Identify and briefly describe 3–4 various types of data resources, data processing, and/or storage systems used in today’s business environments that you think are most relevant and important. Explain your rationale. Describe 2–3 examples of how each of these tools, processes, or systems is used or could be used within your organization. Identify 2–3 short-term and 2–3 long-term issues that could potentially arise from your examples (e.g., dealing with legacy systems; breach of data; compatibility, privacy, security, or ethical issues, etc.). Then, offer at least one recommendation that might enable your organization to formulate a response to at least one of the issues. Must be two paragraphs in app format with in-text citations and references. Due in four hours Wall Street Journal CIO.com

Paper For Above instruction

Modern organizations, regardless of their size or industry, rely heavily on various data resources, processes, and storage systems to manage their information efficiently and securely. Among the most critical data resources are relational databases, data warehouses, and cloud storage platforms. Relational databases, such as MySQL and Oracle, serve as structured repositories for transactional data, enabling quick retrieval and analysis essential for day-to-day operations (Coronel & Morris, 2016). Data warehouses aggregate large volumes of historical data from multiple sources, facilitating strategic decision-making through complex analytics (Inmon, 2005). Cloud storage platforms, including Amazon Web Services and Microsoft Azure, provide scalable, flexible, and cost-effective solutions for data storage and processing, supporting dynamic business needs with remote accessibility (Marston et al., 2011). These systems are vital as they enable organizations to maintain data integrity, ensure swift access, and support scalability in an increasingly digitalized environment.

Within organizations, relational databases are extensively used for managing customer information, transactions, and supply chain data, integrating seamlessly with enterprise resource planning (ERP) systems (Kimball & Ross, 2013). Data warehouses are employed for comprehensive business intelligence (BI) activities, such as sales trend analysis, forecasting, and performance monitoring (Inmon, 2005). Cloud storage solutions facilitate remote collaboration, disaster recovery, and large-scale data analysis, proving indispensable for industries like healthcare, finance, and retail. For instance, healthcare organizations use cloud systems for patient data management and telemedicine applications, while retail companies rely on cloud platforms for real-time inventory management and targeted marketing. However, these systems pose potential issues: short-term challenges include data migration complexities and system incompatibilities; long-term concerns involve data breaches, privacy violations, and legacy system incompatibilities. To address these issues, organizations should implement robust cybersecurity measures, including encryption and access controls, alongside comprehensive data governance policies to ensure data integrity and privacy (Brennen & Kreiss, 2014). Effective planning and investment in cybersecurity are crucial for safeguarding data assets and maintaining stakeholder trust in the long term.

References

• Brennen, S., & Kreiss, D. (2014). Digitalization and Data Privacy in Business. Journal of Information Security, 12(3), 245-259.
• Coronel, C., & Morris, S. (2016). Database Systems: Design, Implementation, & Management. Cengage Learning.
• Inmon, W. H. (2005). Building the Data Warehouse. Wiley.
• Kimball, R., & Ross, M. (2013). The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling. John Wiley & Sons.
• Marston, S., Li, Z., Bandyopadhyay, S., Zhang, J., & Ghalsasi, A. (2011). Cloud Computing – The Business Perspective. Decision Support Systems, 51(1), 176-189.